Sunday, February 26, 2017

More quick links

Some of the tech news I found interesting lately, and you might too:

"In addition to making our systems more intelligent, we have to make them more intelligible too ... AI systems to augment human capabilities ... A human-centered approach is more important than ever." ([1])

"Understanding the brain is a fascinating problem but ... separate from the goal of AI which is solving problems ... We don’t need to duplicate humans ... We want humans and machines to partner and do something that they cannot do on their own." ([1])

"Machine learning and reasoning to help doctors to understand patient outcomes -- in advance of poor outcomes ... a great deal of low-hanging fruit where even today’s AI technologies are well positioned to help ... error detection, alerting, and decision support ... could save hundreds of thousands of lives per year" ([1][2])

Not sure how well known this is: "Facebook collects information about pages [you] visit that contain Facebook sharing buttons ... And in case that wasn’t enough, Facebook also buys data about its users’ mortgages, car ownership and shopping habits from some of the biggest commercial data brokers. Facebook uses all this data to offer marketers a chance to target ads to increasingly specific groups of people. Indeed, we found Facebook offers advertisers more than 1,300 categories for ad targeting — everything from people whose property size is less than .26 acres to households with exactly seven credit cards." ([1])

Interesting example for the news industry: "Doubling down on traditional journalism and investing heavily in new ways to deliver it, through smartphone apps, voice-activated speakers and e-readers. The Post’s digital effort has become the envy of the industry, with as many as 80 software engineers, developers and others working alongside reporters and editors to present the news in real time." ([1])

"Bezos has worked to create a culture at Amazon that’s hospitable to experimentation ... developing products customers will actually want to pay for ... experiments start small and grow over time ... a small team to experiment with the idea and find out if it’s viable ... if a team succeeds in smaller challenges, it’s given more resources and a larger challenge to tackle ... prioritize launching early over everything else ... learn as quickly as possible whether an idea that sounds good on paper is actually a good idea in the real world ... getting a product into the hands of paying customers as quickly as possible and taking their feedback seriously ... avoids wasting years working on products that don’t serve the needs of real customers." ([1])

"Many failed ideas have been resuscitated and rebranded as successful products and services, owned and managed by people other than their originators. Behind almost every popular app or website today lie numerous shadow versions that have been sloughed away by time. Yet recognition of the group nature of the enterprise would undermine a myth that legitimizes the consolidation of profit, for the most part, among a small group of people." ([1])

For those of us tracking virtual reality: "While Facebook does not provide sales figures for the $599 Oculus Rift headset ... analysts believe they are slow. One research firm ... estimated the company sold only about 355,000 by the end of last year."﻿ ([1][2][3])

A surprising level of detail here on what software development is like inside of Google. I agree with most of it, and highly recommend reading at least Section 2. ([1][2])

Great blog post summarizing NIPS 2016. Highlights are what wins Kaggle competitions, why deep learning works, latest twiddles to deep learning and reinforcement learning, why dialogs (chat) still doesn't work, and that Baidu has products who's only value is in the data they collect (not direct revenue, just the explore part of explore/exploit, learning how to be more effective). ([1])

Ease of use is badly underrated: "Using TensorFlow makes me feel like I’m not smart enough to use TensorFlow; whereas using Keras makes me feel like neural networks are easier than I realized." ([1])

New paper by Geoff Hinton and Jeff Dean, essentially a very large ensemble of neural networks with sparsity enforced to minimize the computational cost ([1])

Different people we work with in tech tend to have different ideas of what it means to get things done ([1])

"People with different backgrounds bring new information. Simply interacting with individuals who are different forces group members to prepare better, to anticipate alternative viewpoints and to expect that reaching consensus will take effort." ([1])

Meetings are expensive -- a 10 person meeting for an hour costs a few thousand dollars -- and people hate meetings too. Some good reoccurring themes here are to keep meetings small, short, write a tight agenda ahead of time, stay off your laptop and phone, and try to finish early. ([1])

Disappointing game theory tidbit of the day, the Joy of Destruction game shows people enjoy causing harm when they can do it without consequences ([1][2])

Great data visualizations from 538, not just eye candy but convey information quickly ([1])

"Tesla has 1.3 billion miles of car-driving data thanks to its Autopilot-equipped vehicles that are already on the road before competitors in Detroit and Silicon Valley can roll self-driving cars off the lot. It’s a massive competitive advantage." ([1])

Impressive plans from China's space program, probes on the far side of the moon and on Mars in the next four years ([1])

For those interested in education, MIT's popular and excellent Scratch has published a dataset of how people learn computational thinking ([1])

What Code.org has achieved is very impressive: "Trained 50,000 new K-12 computer science teachers ... More than 20 million lines of code have been written by ... more than one million K-12 students ... we expect to dramatically change the demographics of AP Computer Science this year" ([1])

Funny article from The Onion on having too many browser tabs open ([1])